114 citations · 205 across the 9 of their papers we have counts for
9 papers
PLaMo 2 Technical Report
Preferred Networks, :, Kaizaburo Chubachi +24
In this report, we introduce PLaMo 2, a series of Japanese-focused large language models featuring a hybrid Samba-based architecture that transitions to full attention via continua…
Joint Search of Data Augmentation Policies and Network Architectures
Taiga Kashima, Yoshihiro Yamada, Shunta Saito
The common pipeline of training deep neural networks consists of several building blocks such as data augmentation and network architecture selection. AutoML is a research field th…
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score
He Huang, Shunta Saito, Yuta Kikuchi +3
Scene graph parsing aims to detect objects in an image scene and recognize their relations. Recent approaches have achieved high average scores on some popular benchmarks, but fail…
Chainer: A Deep Learning Framework for Accelerating the Research Cycle
Seiya Tokui, Ryosuke Okuta, Takuya Akiba +7
Software frameworks for neural networks play a key role in the development and application of deep learning methods. In this paper, we introduce the Chainer framework, which intend…
Train Sparsely, Generate Densely: Memory-efficient Unsupervised Training of High-resolution Temporal GAN
Masaki Saito, Shunta Saito, Masanori Koyama +1
Training of Generative Adversarial Network (GAN) on a video dataset is a challenge because of the sheer size of the dataset and the complexity of each observation. In general, the…
Minimizing Supervision for Free-space Segmentation
Satoshi Tsutsui, Tommi Kerola, Shunta Saito +1
Identifying "free-space," or safely driveable regions in the scene ahead, is a fundamental task for autonomous navigation. While this task can be addressed using semantic segmentat…